Bruno Olshausen, “Perception as Inference”

/ August 9, 2021/

October 12, 2021 @ 12:00 pm – 1:00 pm

Bruno OIshausen, PhD


Neuroscience and Optometry

University of California, Berkeley

Title: “Perception as Inference”

Abstract:  Our subjective experience of the visual world is nothing like the 2D images sensed by our retinae.  We experience a stable world full of well-defined geometric shapes and object boundaries, 3D surfaces with continuous shading and reflectance along with their material properties, yet the retinal image is highly unstable, discretely sampled by a highly non-uniform lattice of retinal ganglion cells, and relayed to the cortex via punctate spike trains.  How do we explain this?  I shall present the point of view that our subjective experience is a mostly correct hallucination about the external world which the brain works very hard to create.  It may be understood in mechanistic terms by expanding upon Helmholtz’s notion of ‘perception as inference’ using the mathematical framework of Bayesian inference. I will describe three example of this approach:  a computational model for how the cortex achieves high-acuity visual representations from fixational drift motion, the robustness of sparse coding to adversarial perturbations, and a hierarchical Bayesian inference model of visual cortex.

Biography: Bruno OIshausen is Professor of Neuroscience and Optometry at the University of California, Berkeley.  He also serves as Director of the Redwood Center for Theoretical Neuroscience, an interdisciplinary research group focusing on mathematical and computational models of brain function.  He received B.S. and M.S. degrees in Electrical Engineering from Stanford University, and a Ph.D. in Computation and Neural Systems from the California Institute of Technology.  During postdoctoral work with David Field at Cornell he developed the sparse coding model of visual cortex which provides a linking principle between natural scene statistics and the response properties of visual neurons.  Olshausen’s current research aims to understand the information processing strategies employed by the brain for doing tasks such as object recognition and scene analysis.  This work seeks not only to advance our understanding of the brain, but also to discover new algorithms for scene analysis based on how brains work.

Meeting ID: 995 6750 4456

Passcode: Clark

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